In image processing, edge detection and line segment (or spline) extraction are often necessary steps for operations including object detection and recognition. For example, many current face detection methods include edge detection and spline extraction as a part of their operation. Edge detection is used to process a digital image into an edge image, where the edge image comprises only edge pixels. Line segment extraction is then used to process the edge image into a plurality of line segments, or splines. Each spline is a straight line segment without any corners. Splines may contact each other at their end points, but not at any other location within the spline.
Since splines are straight lines, they may be easily described mathematically by a line equation, or simply by defining their end points. This allows further image processing operations to operate efficiently for such purposes as object detection and recognition. Speed and accuracy are critical to any method for spline extraction from edge images. Faster spline extraction methods are useful in particular when analyzing video data where new images are captured at the frame rate of the video source. Accuracy may be critical in many different image processing methods since incorrect splines may render latter image processing operations invalid.